GenAI / Cloud / Terraform Engineer

Role Overview

We are seeking an experienced GenAI / Cloud / Terraform Engineer to design, develop, and deploy enterprise-grade AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, Azure Cloud, and Infrastructure as Code (Terraform). The ideal candidate will have hands-on experience building scalable AI platforms, cloud-native applications, and intelligent automation solutions.

Responsibilities

• Design and develop enterprise AI applications using LLMs, OpenAI, RAG, and AI Agent frameworks.
• Build AI-powered solutions including Copilots, Chatbots, Enterprise Search, Recommendation Engines, and Workflow Automation.
• Develop scalable RAG pipelines using vector databases, embeddings, and semantic search.
• Design and implement AI Agent workflows with LangGraph, CrewAI, AutoGen, Function Calling, and Tool Invocation.
• Build and deploy cloud-native AI applications on Microsoft Azure (AWS experience is acceptable).
• Develop reusable Terraform modules and automate infrastructure provisioning.
• Build REST APIs and AI integration services, including MCP Server implementations.
• Ensure application security, monitoring, scalability, and operational excellence.
• Collaborate with cross-functional teams to deliver enterprise AI solutions.

Requirements

• 6+ years of overall IT experience.
• 3+ years of hands-on experience in Generative AI.
• 5+ years of experience with Azure, AWS, or GCP.
• 2+ years of experience with Terraform (Infrastructure as Code).
• Strong expertise in LLMs, OpenAI, RAG, AI Agents, and Prompt Engineering.
• Experience with LangGraph, CrewAI, AutoGen, or similar agent frameworks.
• Strong programming skills in Python, .NET, or Node.js.
• Experience with Vector Databases, Semantic Search, and REST API Development.
• Experience with Azure OpenAI, Azure AI Foundry, Azure AI Search, or similar AI services is preferred.
• Preferred skills include Kubernetes (AKS/EKS), Docker, CI/CD pipelines, GitHub Actions or Azure DevOps, RAGAS, DeepEval, LoRA / QLoRA fine-tuning techniques, and monitoring tools such as Splunk.
• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
• Strong analytical, problem-solving, and communication skills.
• Experience working in Agile development environments.